The field of the present invention relates to an image processing apparatus, an image processing method, a magnetic resonance imaging apparatus, and a program for use in image processing. More particularly, the present invention relates to an image processing apparatus, an image processing method, a magnetic resonance imaging apparatus, and a program for performing an imaging process on an original image obtained so as to include a connection figure having a plurality of figures connected to each other, thereby generating an extraction image of a figure to be extracted in the plurality of figures.
An imaging apparatus such as a magnetic resonance imaging (MRI) apparatus is an apparatus for obtaining an image of a subject and displaying the image on a screen and is often used for medical purposes.
In the magnetic resonance imaging apparatus, an imaging region in a subject is placed in an imaging space in which static magnetic fields are generated, and spins of protons in the imaging region are aligned in the direction of the static magnetic fields, thereby generating a magnetization vector. By applying an RF pulse of resonance frequency, the nuclear magnetic resonance phenomenon is caused to flip the spins and change the magnetization vector of the protons. After that, a magnetic resonance (MR) signal generated when the flipped proton returns to the original state of the magnetization vector is received. On the basis of the received magnetic resonance signal, an image such as a slice image of the imaging region is reconstructed.
In the magnetic resonance imaging apparatus, to obtain information of the extending direction of a fiber such as a nerve fiber bundle in a subject, the head of the subject is scanned by the DTI (Diffusion Tensor Imaging), and DTI data set is generated. For example, the DTI data set is generated so as to have a DTI image including a T2 image and an ADC (Apparent Diffusion Coefficient) image. To clarify the positional relation between the nerve fiber bundle and the tumor and accurately execute an operation plan, the figure expressing the tumor is accurately extracted from the DTI image obtained as described above by segmentation. After that, by using the extraction image including the figure expressing the tumor, fusion display is performed. For example, noise is eliminated from the DTI image by using an anisotropic diffusion filter (refer to, for example, non-patent document 1), a figure expressing a tumor is extracted by segmentation according to, for example, the fast marching level set method (refer to, for example, non-patent document 2), and fusion display is performed with the extraction image obtained by extracting the figure expressing the tumor by segmentation.
In the DTI image obtained, however, the pixel values of the figure expressing the tumor and those of a cerebral ventricle filled with CSF are almost the same. When the tumor and the cerebral ventricle are close to each other or in contact with each other, in some cases, their figures are extracted from the DTI image in a state where the plural figures showing the tumor and the cerebral ventricle are connected to each other. Therefore, at the time of performing the fusion display by using the extraction image, not only the figure expressing the tumor but also the other figures of the cerebral ventricle and the like are included in the extraction image. There are cases such that it is difficult for the operator who observes the fusion-displayed image to clearly grasp the positional relation between a nerve fiber bundle and a tumor and appropriately execute an operation plan.
Consequently, methods of solving the problem by executing imaging processes on the DTI image have been proposed.
Concretely, a method of generating an extraction image in which only a tumor is extracted has been proposed, by preliminarily scanning the head with a pulse sequence of the FLAIR (fluid attenuated IR) method, generating an image in which contrast occurs between a cerebral ventricle and a tumor, obtaining the positional information of pixels corresponding only to the cerebral ventricle and, after that, performing an imaging process of masking the pixel portion corresponding to the cerebral ventricle in the DTI image obtained as described above (refer to, for example, non-patent document 3).
In another method, a segmentation process is executed on a DTI image having a connection figure including a plurality of figures connected to each other to selectively extract the connection figure. After that, by sequentially performing erosion (reducing) process and dilation (expanding) process in the morphologic operation, the connection figure is divided into a figure of a tumor and a figure of a cerebral ventricle. After that, a segmentation of only the figure expressing the tumor is performed from the image having the separated figures (refer to, for example, non-patent document 4).    Non-patent document 1. G. Gerig et. A1, IEEE trans Med. Imaging, 11(2), 221-232, 1992.    Non-patent document 2. J. A. Sethian, Level set method and fast marching method, Cambridge University Press, 1999.    Non-patent document 3. S. Saraswathy et. A1, ISMRM 2006, p. 1609.    Non-patent document 4. Toriwaki et. A1, Image Information Process (1), pp. 73-76, Corona Publishing Co., Ltd. 2005.
In the former case, however, it is necessary to perform a scan with a pulse sequence of the FLAIR method or the like in addition to a scan for generating a DTI image. Consequently, time required for the scans is long and, in some cases, diagnosis cannot be efficiently conducted.
In the latter case, in some cases, a part of the topology of the tumor in the DTI image is lost due to execution of the erosion process and the dilation process in the morphological operation. That is, there is the case that the shape of the tumor in the DTI image and that in an image obtained after the erosion process and the dilation process differ from each other. In this case, it is not easy to appropriately extract only the tumor, and diagnosis cannot be efficiently conducted.
As described above, it is difficult to obtain an extraction image by properly and efficiently extracting a figure to be extracted from an original image having a connection figure in which a plurality of figures of, for example, a tumor and a cerebral ventricle in the DTI image are connected to each other.